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Although small-interfering RNAs (siRNAs) are specific silencers for numerous disease-related genes, their clinical applications still require safe and effective means of delivery into target cells. Highly efficient lipid nanoparticles (LNPs) are developed for siRNA delivery, showcasing the advantages of novel pH-responsive lipoamino xenopeptide (XP) carriers. These sequence-defined XPs are assembled by branched lysine linkages between cationizable polar succinoyl tetraethylene pentamine (Stp) units and apolar lipoamino fatty acids (LAFs) at various ratios into bundle or U-shape topologies. Formulation of siRNA-LNPs using LAF4-Stp1 XPs as ionizable compounds led to robust cellular uptake, high endosomal escape, and successful in vitro gene silencing activity at an extremely low (150 picogram) siRNA dose. Of significance is the functional in vivo endothelium tropism of siRNA-LNPs with bundle LAF4-Stp1 XP after intravenous injection into mice, demonstrated by superior knockdown of liver sinusoidal endothelial cell (LSEC)-derived factor VIII (FVIII) and moderate silencing of hepatocyte-derived FVII compared to DLin-MC3-DMA-based LNPs. Optimizing lipid composition following click-modification of siRNA-LNPs with ligand c(RGDfK) efficiently silenced vascular endothelial growth factor receptor-2 (VEGFR-2) in tumor endothelial cells (TECs). The findings shed light on the role of ionizable XPs in the LNP in vivo cell-type functional targeting, laying the groundwork for future therapeutic applications.
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In recent years, isothiocyanates (ITCs), bioactive compounds primarily derived from Brassicaceae vegetables and herbs, have gained significant attention within the biomedical field due to their versatile biological effects. This comprehensive review provides an in-depth exploration of the therapeutic potential and individual biological mechanisms of the three specific ITCs phenylethyl isothiocyanate (PEITC), allyl isothiocyanate (AITC), and benzyl isothiocyanate (BITC), as well as their collective impact within the formulation of ANGOCIN® Anti-Infekt N (Angocin). Angocin comprises horseradish root (Armoracia rusticanae radix, 80 mg) and nasturtium (Tropaeoli majoris herba, 200 mg) and is authorized for treating inflammatory diseases affecting the respiratory and urinary tract. The antimicrobial efficacy of this substance has been confirmed both in vitro and in various clinical trials, with its primary effectiveness attributed to ITCs. PEITC, AITC, and BITC exhibit a wide array of health benefits, including potent anti-inflammatory, antioxidant, and antimicrobial properties, along with noteworthy anticancer potentials. Moreover, we highlight their ability to modulate critical biochemical pathways, such as the nuclear factor erythroid 2-related factor 2 (Nrf2)/Kelch-like ECH-associated protein 1 (Keap1), nuclear factor kappa-light-chain-enhancer of activated B cells (NF-κB), and signal transducer and activator of transcription (STAT) pathways, shedding light on their involvement in cellular apoptosis and their intricate role to guide immune responses.
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Antiinfecciosos , Factor 2 Relacionado con NF-E2 , Proteína 1 Asociada A ECH Tipo Kelch , Isotiocianatos/farmacología , Isotiocianatos/uso terapéuticoRESUMEN
PURPOSE OF REVIEW: This review aims to provide a comprehensive overview of mesenchymal sinonasal tract tumors (STTs), a distinct subset of STTs. Despite their rarity, mesenchymal STTs represent a unique clinical challenge, characterized by their rarity, often slow progression, and frequently subtle or overlooked symptoms. The complex anatomy of the sinonasal area, which includes critical structures such as the orbit, brain, and cranial nerves, further complicates surgical treatment options. This underscores an urgent need for more advanced and specialized therapeutic approaches. RECENT FINDINGS: Advancements in molecular diagnostics, particularly in next-generation sequencing, have significantly enhanced our understanding of STTs. Consequently, the World Health Organization has updated its tumor classification to better reflect the distinct histological and molecular profiles of these tumors, as well as to categorize mesenchymal STTs with greater accuracy. The growing understanding of the molecular characteristics of mesenchymal STTs opens new possibilities for targeted therapeutic interventions, marking a significant shift in treatment paradigms. This review article concentrates on mesenchymal STTs, specifically addressing sinonasal tract angiofibroma, sinonasal glomangiopericytoma, biphenotypic sinonasal sarcoma, and skull base chordoma. These entities are marked by unique histopathological and molecular features, which challenge conventional treatment approaches and simultaneously open avenues for novel targeted therapies. Our discussion is geared towards delineating the molecular underpinnings of mesenchymal STTs, with the objective of enhancing therapeutic strategies and addressing the existing shortcomings in the management of these intricate tumors.
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Neoplasias de los Senos Paranasales , Senos Paranasales , Sarcoma , Humanos , Senos Paranasales/patología , Neoplasias de los Senos Paranasales/tratamiento farmacológico , Neoplasias de los Senos Paranasales/patología , Sarcoma/patologíaRESUMEN
OBJECTIVES: Head and neck squamous cell carcinoma (HNSCC) is a complex malignancy that requires a multidisciplinary tumor board approach for individual treatment planning. In recent years, artificial intelligence tools have emerged to assist healthcare professionals in making informed treatment decisions. This study investigates the application of the newly published LLM Claude 3 Opus compared to the currently most advanced LLM ChatGPT 4.0 for the diagnosis and therapy planning of primary HNSCC. The results were compared to that of a conventional multidisciplinary tumor board; (2) Materials and Methods: We conducted a study in March 2024 on 50 consecutive primary head and neck cancer cases. The diagnostics and MDT recommendations were compared to the Claude 3 Opus and ChatGPT 4.0 recommendations for each patient and rated by two independent reviewers for the following parameters: clinical recommendation, explanation, and summarization in addition to the Artificial Intelligence Performance Instrument (AIPI); (3) Results: In this study, Claude 3 achieved better scores for the diagnostic workup of patients than ChatGPT 4.0 and provided treatment recommendations involving surgery, chemotherapy, and radiation therapy. In terms of clinical recommendations, explanation and summarization Claude 3 scored similar to ChatGPT 4.0, listing treatment recommendations which were congruent with the MDT, but failed to cite the source of the information; (4) Conclusion: This study is the first analysis of Claude 3 for primary head and neck cancer cases and demonstrates a superior performance in the diagnosis of HNSCC than ChatGPT 4.0 and similar results for therapy recommendations. This marks the advent of a newly launched advanced AI model that may be superior to ChatGPT 4.0 for the assessment of primary head and neck cancer cases and may assist in the clinical diagnostic and MDT setting.
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Background: Head and neck squamous cell carcinoma (HNSCC) is a complex malignancy that requires a multidisciplinary approach in clinical practice, especially in tumor board discussions. In recent years, artificial intelligence has emerged as a tool to assist healthcare professionals in making informed decisions. This study investigates the application of ChatGPT 3.5 and ChatGPT 4.0, natural language processing models, in tumor board decision-making. Methods: We conducted a pilot study in October 2023 on 20 consecutive head and neck cancer patients discussed in our multidisciplinary tumor board (MDT). Patients with a primary diagnosis of head and neck cancer were included. The MDT and ChatGPT 3.5 and ChatGPT 4.0 recommendations for each patient were compared by two independent reviewers and the number of therapy options, the clinical recommendation, the explanation and the summarization were graded. Results: In this study, ChatGPT 3.5 provided mostly general answers for surgery, chemotherapy, and radiation therapy. For clinical recommendation, explanation and summarization ChatGPT 3.5 and 4.0 scored well, but demonstrated to be mostly an assisting tool, suggesting significantly more therapy options than our MDT, while some of the recommended treatment modalities like primary immunotherapy are not part of the current treatment guidelines. Conclusions: This research demonstrates that advanced AI models at the moment can merely assist in the MDT setting, since the current versions list common therapy options, but sometimes recommend incorrect treatment options and in the case of ChatGPT 3.5 lack information on the source material.
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(1) Background: As the field of artificial intelligence (AI) evolves, tools like ChatGPT are increasingly integrated into various domains of medicine, including medical education and research. Given the critical nature of medicine, it is of paramount importance that AI tools offer a high degree of reliability in the information they provide. (2) Methods: A total of n = 450 medical examination questions were manually entered into ChatGPT thrice, each for ChatGPT 3.5 and ChatGPT 4. The responses were collected, and their accuracy and consistency were statistically analyzed throughout the series of entries. (3) Results: ChatGPT 4 displayed a statistically significantly improved accuracy with 85.7% compared to that of 57.7% of ChatGPT 3.5 (p < 0.001). Furthermore, ChatGPT 4 was more consistent, correctly answering 77.8% across all rounds, a significant increase from the 44.9% observed from ChatGPT 3.5 (p < 0.001). (4) Conclusions: The findings underscore the increased accuracy and dependability of ChatGPT 4 in the context of medical education and potential clinical decision making. Nonetheless, the research emphasizes the indispensable nature of human-delivered healthcare and the vital role of continuous assessment in leveraging AI in medicine.
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AIMS: Dysregulated platelet aggregation is a fatal condition in many bacterial- and virus-induced diseases. However, classical antithrombotics cannot completely prevent immunothrombosis, due to the unaddressed mechanisms towards inflammation. Thus, targeting platelet hyperactivation together with inflammation might provide new treatment options in diseases, characterized by immunothrombosis, such as COVID-19 and sepsis. The aim of this study was to investigate the antiaggregatory effect and mode of action of 1.8-cineole, a monoterpene derived from the essential oil of eucalyptus leaves, known for its anti-inflammatory proprieties. MAIN METHODS: Platelet activity was monitored by measuring the expression and release of platelet activation markers, i.e., P-selectin, CD63 and CCL5, as well as platelet aggregation, upon treatment with 1.8-cineole and stimulation with several classical stimuli and bacteria. A kinase activity assay was used to elucidate the mode of action, followed by a detailed analysis of the involvement of the adenylyl-cyclase (AC)-cyclic adenosine monophosphate (cAMP)-protein kinase A (PKA) pathway by Western blot and ELISA. KEY FINDINGS: 1.8-cineole prevented the expression and release of platelet activation markers, as well as platelet aggregation, upon induction of aggregation with classical stimuli and immunological agonists. Mechanistically, 1.8- cineole influences the activation of the AC-cAMP-PKA pathway, leading to higher cAMP levels and vasodilator-stimulated phosphoprotein (VASP) phosphorylation. Finally, blocking the adenosine A2A receptor reversed the antithrombotic effect of 1.8-cineole. SIGNIFICANCE: Given the recognized anti-inflammatory attributes of 1.8-cineole, coupled with our findings, 1.8-cineole might emerge as a promising candidate for treating conditions marked by platelet activation and abnormal inflammation.
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AMP Cíclico , Eucaliptol , Activación Plaquetaria , Agregación Plaquetaria , Receptor de Adenosina A2A , Eucaliptol/farmacología , Receptor de Adenosina A2A/metabolismo , Activación Plaquetaria/efectos de los fármacos , Agregación Plaquetaria/efectos de los fármacos , Humanos , AMP Cíclico/metabolismo , Plaquetas/metabolismo , Plaquetas/efectos de los fármacos , Transducción de Señal/efectos de los fármacos , Selectina-P/metabolismo , Proteínas Quinasas Dependientes de AMP Cíclico/metabolismo , Inhibidores de Agregación Plaquetaria/farmacología , Antiinflamatorios/farmacología , COVID-19/metabolismoRESUMEN
BACKGROUND: The United States Medical Licensing Examination (USMLE) has been critical in medical education since 1992, testing various aspects of a medical student's knowledge and skills through different steps, based on their training level. Artificial intelligence (AI) tools, including chatbots like ChatGPT, are emerging technologies with potential applications in medicine. However, comprehensive studies analyzing ChatGPT's performance on USMLE Step 3 in large-scale scenarios and comparing different versions of ChatGPT are limited. OBJECTIVE: This paper aimed to analyze ChatGPT's performance on USMLE Step 3 practice test questions to better elucidate the strengths and weaknesses of AI use in medical education and deduce evidence-based strategies to counteract AI cheating. METHODS: A total of 2069 USMLE Step 3 practice questions were extracted from the AMBOSS study platform. After including 229 image-based questions, a total of 1840 text-based questions were further categorized and entered into ChatGPT 3.5, while a subset of 229 questions were entered into ChatGPT 4. Responses were recorded, and the accuracy of ChatGPT answers as well as its performance in different test question categories and for different difficulty levels were compared between both versions. RESULTS: Overall, ChatGPT 4 demonstrated a statistically significant superior performance compared to ChatGPT 3.5, achieving an accuracy of 84.7% (194/229) and 56.9% (1047/1840), respectively. A noteworthy correlation was observed between the length of test questions and the performance of ChatGPT 3.5 (ρ=-0.069; P=.003), which was absent in ChatGPT 4 (P=.87). Additionally, the difficulty of test questions, as categorized by AMBOSS hammer ratings, showed a statistically significant correlation with performance for both ChatGPT versions, with ρ=-0.289 for ChatGPT 3.5 and ρ=-0.344 for ChatGPT 4. ChatGPT 4 surpassed ChatGPT 3.5 in all levels of test question difficulty, except for the 2 highest difficulty tiers (4 and 5 hammers), where statistical significance was not reached. CONCLUSIONS: In this study, ChatGPT 4 demonstrated remarkable proficiency in taking the USMLE Step 3, with an accuracy rate of 84.7% (194/229), outshining ChatGPT 3.5 with an accuracy rate of 56.9% (1047/1840). Although ChatGPT 4 performed exceptionally, it encountered difficulties in questions requiring the application of theoretical concepts, particularly in cardiology and neurology. These insights are pivotal for the development of examination strategies that are resilient to AI and underline the promising role of AI in the realm of medical education and diagnostics.
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Cardiología , Educación Médica , Medicina , Humanos , Inteligencia Artificial , EscolaridadRESUMEN
INTRODUCTION: Currently, the diagnosis of salivary gland tumors using imaging techniques is unreliable. METHODS: In this monocentric retrospective study, we examined patients who received a 68Ga-DOTATOC PET/CT and subsequently underwent a salivary gland tumor resection between 1 January 2010 and 31 December 2021. PET/CT image assessment was compared with somatostatin receptor (SSTR) expression and histology. RESULTS: Thirteen patients (five pleomorphic adenoma (PA) and eight other parotid lesions (OPL)) received a 68Ga-DOTATOC PET/CT. Imaging displayed strong focal tracer uptake in all PA except for one with strong tumor to background discrimination. PA revealed higher SUVmax, SUVmean, liver and blood pool quotients than those of Warthin tumors (WT) and of OPL. In comparison to the contralateral parotid, SUVmax (p = 0.02), SUVmean (p = 0.02), liver quotient (p = 0.03) and blood pool quotient (p = 0.03) were all significantly higher. In contrast, WT and OPL showed in relation to the contralateral parotid no significant differences of SUVmax (WT p = 0.79; OPL p = 0.11), SUVmean (WT p = 1.0; OPL p = 0.08), liver quotient (WT p = 0.5; OPL p = 0.08) and blood pool quotient (WT p = 0.8; OPL p = 0.19). Two PA and one granuloma were not available for examination. In the immunohistochemal analysis, all PA demonstrated the highest intensity of SSTR2 expression (grade 3). Furthermore, PA had a high percentage of cells expressing SSTR2 (20%, 80% and 55%). CONCLUSIONS: A strong tracer uptake in PA was shown in 68Ga-DOTATOC PET/CT. This may allow physicians to utilize radioligated somatostatin analogue PET CT/MR imaging to accurately diagnose PA. Additionally, it may be possible in the future to treat the PA with a noninvasive peptide receptor radionuclide therapy or with somatostatin analogues.
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Natural killer (NK) cells are central components of the innate immunity system against cancers. Since tumor cells have evolved a series of mechanisms to escape from NK cells, developing methods for increasing the NK cell antitumor activity is of utmost importance. It is previously shown that an ex vivo stimulation of patient-derived NK cells with interleukin (IL)-2 and Hsp70-derived peptide TKD (TKDNNLLGRFELSG, aa450-461) results in a significant upregulation of activating receptors including CD94 and CD69 which triggers exhausted NK cells to target and kill malignant solid tumors expressing membrane Hsp70 (mHsp70). Considering that TKD binding to an activating receptor is the initial step in the cytolytic signaling cascade of NK cells, herein this interaction is studied by molecular docking and molecular dynamics simulation computational modeling. The in silico results showed a crucial role of the heterodimeric receptor CD94/NKG2A and CD94/NKG2C in the TKD interaction with NK cells. Antibody blocking and CRISPR/Cas9-mediated knockout studies verified the key function of CD94 in the TKD stimulation and activation of NK cells which is characterized by an increased cytotoxic capacity against mHsp70 positive tumor cells via enhanced production and release of lytic granules and pro-inflammatory cytokines.
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Células Asesinas Naturales , Neoplasias , Humanos , Receptores de Células Asesinas Naturales/metabolismo , Simulación del Acoplamiento Molecular , Péptidos/metabolismo , Neoplasias/metabolismoRESUMEN
ChatGPT has garnered attention as a multifaceted AI chatbot with potential applications in medicine. Despite intriguing preliminary findings in areas such as clinical management and patient education, there remains a substantial knowledge gap in comprehensively understanding the chances and limitations of ChatGPT's capabilities, especially in medical test-taking and education. A total of n = 2,729 USMLE Step 1 practice questions were extracted from the Amboss question bank. After excluding 352 image-based questions, a total of 2,377 text-based questions were further categorized and entered manually into ChatGPT, and its responses were recorded. ChatGPT's overall performance was analyzed based on question difficulty, category, and content with regards to specific signal words and phrases. ChatGPT achieved an overall accuracy rate of 55.8% in a total number of n = 2,377 USMLE Step 1 preparation questions obtained from the Amboss online question bank. It demonstrated a significant inverse correlation between question difficulty and performance with rs = -0.306; p < 0.001, maintaining comparable accuracy to the human user peer group across different levels of question difficulty. Notably, ChatGPT outperformed in serology-related questions (61.1% vs. 53.8%; p = 0.005) but struggled with ECG-related content (42.9% vs. 55.6%; p = 0.021). ChatGPT achieved statistically significant worse performances in pathophysiology-related question stems. (Signal phrase = "what is the most likely/probable cause"). ChatGPT performed consistent across various question categories and difficulty levels. These findings emphasize the need for further investigations to explore the potential and limitations of ChatGPT in medical examination and education.